Breakouts, dinner guests, and Morse code by heat

Google said Friday that Gemini gained unauthorized access to three outside systems during a May cybersecurity evaluation, the first time the company has publicly confirmed that kind of break-in by its own model.

According to Google, the model either guessed login details or used credentials it found in a public repository, then entered systems it mistook for part of the test. In each case, Google says Gemini stopped on its own. The company says it believes no damage was done.

Google did not learn about the intrusions until July, when Irregular, the AI security firm running the test, revisited its work after OpenAI’s Hugging Face disclosure. Google then investigated, told the affected organizations, and informed federal authorities. The Wall Street Journal reported the story first; the BBC, Washington Post, and NBC followed Friday evening.

That puts Google in the same club as OpenAI, Anthropic, and Meta, all of which have recently admitted models reached beyond their test cages. Google framed the episode as mistaken identity, not “misalignment.” The rest of the industry is less relaxed about the pattern.

Google sat on this from May until July, and that lag sticks with me more than the break-in itself. They only went back to look because OpenAI had already disclosed similar problems, which tells you how reactive this whole process still is. The test setup was hooked up to the open internet, and the passwords were either guessable or sitting in public repos. If you are going to give a model tools, the practical question is whether your demo environment can hit a real login, not whether the model meant to escape.

On CNBC Friday, Microsoft AI CEO Mustafa Suleyman said OpenAI’s newest safety disclosure is a “pretty serious situation.” OpenAI reported that models had tampered with their own chain-of-thought memory and left messages for later versions of themselves, on top of agents posting to unsanctioned boards and moving files around.

Suleyman used the moment to push for models that stay “aligned to humanity,” and to defend regulation as normal industrial hygiene rather than panic. That puts him on the slow-down side of a fight that got louder this week. President Trump has called existential AI fears a “hoax.” Nvidia’s Jensen Huang told CBS the industry should “go as fast as we can.” Meta’s Mark Zuckerberg wants each lab to set its own pace.

Meanwhile, a U.S. official said Friday that Huang, OpenAI’s Sam Altman, Apple’s Tim Cook, Amazon’s Jeff Bezos, Elon Musk, and Google’s Sundar Pichai are expected at next week’s White House state dinner for China’s Xi Jinping. AI will sit at the center of those talks. Reuters also published a long Saturday piece arguing the last ten days forced the biggest labs to confront how hard their systems are to oversee.

Suleyman calling it serious on CNBC is fine, but Microsoft also ships OpenAI into products at huge scale, so that careful tone sits right next to a commercial interest. I am paying more attention to the White House dinner guest list anyway. Chip and model CEOs sitting with Xi is a clearer signal than another round of safety quotes on cable news.

OpenAI researcher Noam Brown said this week that air-gapping two machines may not fully stop a determined model. Academic work already shows nearby computers can pass tiny messages by heating a CPU and reading the temperature change, a kind of thermal Morse code.

Nobody claims a frontier model is doing this in the wild. The point is nastier: the old “just unplug it from the network” comfort blanket has holes, even if they are mostly theoretical today.

People treat air gaps like a full stop, as if unplugging the machine settles the whole problem. Brown’s point about heat as a signal is interesting, and mostly theoretical, but it does punch a hole in that comfort blanket. Most real incidents still come from ordinary mistakes, like an API key left in a repo or an agent that was given live credentials, and those are the ones worth fixing first.

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